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Mathematical programming formulations of influence diagrams can bridge the gap between representing and solving decision problems. However, they suffer from both modeling and computational limitations. Aiming to address modeling…

Optimization and Control · Mathematics 2025-06-19 Olli Herrala , Tommi Ekholm , Fabricio Oliveira

In this paper, we consider sequential dynamic team decision problems with nonclassical information structures. First, we address the problem from the point of view of a ``manager" who seeks to derive the optimal strategy of the team in a…

Optimization and Control · Mathematics 2024-07-23 Andreas A. Malikopoulos

Stochastic optimal control problems have a long tradition in applied probability, with the questions addressed being of high relevance in a multitude of fields. Even though theoretical solutions are well understood in many scenarios, their…

Statistics Theory · Mathematics 2024-05-28 Sören Christensen , Claudia Strauch , Lukas Trottner

We consider the optimal design of sequential transmission over broadcast channel with nested feedback. Nested feedback means that the channel output of the outer channel is also available at the decoder of the inner channel. We model the…

Information Theory · Computer Science 2010-04-08 Aditya Mahajan

Under the paradigm of caching, partial data is delivered before the actual requests of users are known. In this paper, this problem is modeled as a canonical distributed source coding problem with side information, where the side…

Information Theory · Computer Science 2016-11-17 Chien-Yi Wang , Sung Hoon Lim , Michael Gastpar

In this work, we study the real-time tracking and reconstruction of an information source with the purpose of actuation. A device monitors the state of the information source and transmits status updates to a receiver over a wireless…

Information Theory · Computer Science 2023-02-28 Mehrdad Salimnejad , Marios Kountouris , Nikolaos Pappas

Neural decoding may be formulated as dynamic state estimation (filtering) based on point process observations, a generally intractable problem. Numerical sampling techniques are often practically useful for the decoding of real neural data.…

Neurons and Cognition · Quantitative Biology 2019-01-15 Yuval Harel , Ron Meir , Manfred Opper

The study of the fundamental limits of information systems is a central theme in information theory. Both the traditional analytical approach and the recently proposed computational approach have significant limitations, where the former is…

Information Theory · Computer Science 2022-05-04 Wenjing Chen , Chao Tian

Autonomous systems are increasingly expected to operate in the presence of adversaries, though adversaries may infer sensitive information simply by observing a system. Therefore, present a deceptive sequential decision-making framework…

In quantum Shannon theory, transmission of information is enhanced by quantum features. Up to very recently, the trajectories of transmission remained fully classical. Recently, a new paradigm was proposed by playing quantum tricks on two…

The information spectrum approach gives general formulae for optimal rates of various information theoretic protocols, under minimal assumptions on the nature of the sources, channels and entanglement resources involved. This paper…

Quantum Physics · Physics 2007-05-23 Garry Bowen , Nilanjana Datta

The connection between control algorithms for Markov decision processes and optimization algorithms has been implicitly and explicitly exploited since the introduction of dynamic programming algorithm by Bellman in the 1950s. Recently, this…

Optimization and Control · Mathematics 2025-12-09 Tolga Ok , Arman Sharifi Kolarijani , Mohamad Amin Sharif Kolarijani , Peyman Mohajerin Esfahani

This paper develops an envelope-based approach to establish a link between information and queueing theory. Unlike classical, equilibrium information theory, information envelopes focus on the dynamics of sources and coders, using functions…

Performance · Computer Science 2015-03-19 Ralf Lübben , Markus Fidler

A fundamental question in neuroscience is how the brain creates an internal model of the world to guide actions using sequences of ambiguous sensory information. This is naturally formulated as a reinforcement learning problem under partial…

Machine Learning · Computer Science 2020-11-02 Minhae Kwon , Saurabh Daptardar , Paul Schrater , Xaq Pitkow

Optimal zero-delay coding (quantization) of a vector-valued Markov source driven by a noise process is considered. Using a stochastic control problem formulation, the existence and structure of optimal quantization policies are studied. For…

Optimization and Control · Mathematics 2014-08-11 Tamás Linder , Serdar Yüksel

We propose an information-theoretic framework for analyzing control systems based on the close relationship of controllers to communication channels. A communication channel takes an input state and transforms it into an output state. A…

Data Analysis, Statistics and Probability · Physics 2007-05-23 Hugo Touchette , Seth Lloyd

Understanding brain function, constructing computational models and engineering neural prosthetics require assessing two problems, namely encoding and decoding, but their relation remains controversial. For decades, the encoding problem has…

Neurons and Cognition · Quantitative Biology 2017-01-16 Hugo Gabriel Eyherabide

We revisit the source coding problem for a Markov chain under the assumption that the transmission times and how fast the Markov chain transitions its state happen at the same time-scale. Specifically, we assume that the transmission of…

Information Theory · Computer Science 2025-11-05 Ismail Cosandal , Sennur Ulukus

In this article, we consider a cooperative control problem involving a heterogeneous network of dynamically decoupled continuous-time linear plants. The (output-feedback) controllers for each plant may communicate with each other according…

Optimization and Control · Mathematics 2024-01-09 Mruganka Kashyap , Laurent Lessard

For reliable transmission across a noisy communication channel, classical results from information theory show that it is asymptotically optimal to separate out the source and channel coding processes. However, this decomposition can fall…

Machine Learning · Computer Science 2019-05-15 Kristy Choi , Kedar Tatwawadi , Aditya Grover , Tsachy Weissman , Stefano Ermon
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